The present invention generally relates to a keyword associative document retrieval system, more particularly to a keyword associative document retrieval system capable of retrieving documents which are required by a user.
Recently, information included in documents such as newspapers, magazines, books and treatises has increased so that the frequency of utilization of a large scale data base, such as JOIS, NEED-IR, DIALOG, has been increasing.
For example, "Automatic Classification of Document Using Statistical Method " ( Information Processing Society of Japan, the 36th National Convention's Papers : 1988, 1st term ) discloses a method called a .chi..sup.2 examination. In the .chi..sup.2 examination, documents are automatically classified into predetermined fields by use of a statistical method. In the .chi..sup.2 examination, a .chi..sup.2 value is calculated as an indicator which represents a deviation of an occurrence frequency of a keyword in the fields. The occurrence frequency of the keyword is the frequency with which the keyword occurs in a field. The applied occurrence frequency is normalized on the basis of the theoretical occurrence frequency so that the .chi..sup.2 value is obtained.
In "Quantitative Method ( Hayashi )" published in a newspaper of Toyo Keizai Shinbunsha in 1974, a method, which is one of the statistical methods which uses the .chi..sup.2 value, for searching a relationship among the fields is disclosed.
In these conventional methods in which the documents are retrieved by use of the .chi..sup.2 examination, a large number of fields, each corresponding to one or more keywords, must be determined to correctly retrieve documents which are required by the user. It is thus hard to obtain the .chi..sup.2 values for all the fields.